Motion tracking system and method

ABSTRACT

A motion tracking system and a motion tracking method are provided. The motion tracking system includes three motion sensing apparatuses wearable on the human body portion of a user. In the method, first sensing data is obtained based on motion sensors disposed on the motion sensing apparatuses, and second sensing data is obtained based on wireless signals transmitted between the motion sensing apparatuses. Motion information of the user is determined by a determining factor. The determining factor includes the first sensing data and the second sensing data. Accordingly, the motion of the user can be tracked with improved accuracy.

BACKGROUND OF THE DISCLOSURE 1. Field of the Disclosure

The present disclosure generally relates to a method for tracking themotion of a user, in particular, to a motion tracking system and amotion tracking method.

2. Description of Related Art

To provide intuitive operation on an electronic apparatus (such as agame player, a computer, a smartphone, a smart appliance, etc.), themotion of the user may be detected, to directly operate the electronicapparatus according to the motion of the user.

In conventional technology, some electronic apparatuses may allow humanbody portions (such as hands, legs, head, etc.) of the user to controlthe operation of these electronic apparatuses, and the motion of thesehuman body portions may be tracked. However, these electronicapparatuses merely provide one way to detect the motion of multiplehuman body portions at the same time. For example, a virtual reality(VR) product may provide handheld controllers, and each handheldcontroller includes an inertial measurement unit (IMU) to track themotion of the hands of the user. Sometimes, merely one motion trackingmanner may be limited by its hardware or tracking mechanism, and resultin abnormal or inaccurate tracking results.

SUMMARY OF THE DISCLOSURE

Accordingly, the present disclosure is directed to a motion trackingsystem and a motion tracking method, in which one human body portionscan be tracked with different motion tracking technologies.

In one of the exemplary embodiments, a motion tracking method is adaptedfor a motion tracking system including first, second and third motionsensing apparatuses wearable on human body portions of a user. Themotion tracking method includes, but not limited to, the followingsteps. First sensing data is obtained based on the motion sensordisposed on the first, second and third motion sensing apparatuses.Second sensing data is obtained based on wireless signals transmittedbetween the first, second and third motion sensing apparatuses. Motioninformation of the user is determined according to a determining factorincluding the first sensing data and the second sensing data.

In one of the exemplary embodiments, a motion tracking system includes,but not limited to, three motion sensing apparatuses and a processor.The motion sensing apparatuses are wearable on the human body portionsof a user. Each motion sensing apparatus includes a wireless transceiverand a motion sensor. The wireless transceiver is used for transmittingor receiving wireless signals. The motion sensor is used for sensing themotion of one human body portion of the user. The processor isconfigured to obtain first sensing data based on the motion sensor ofthe motion sensing apparatuses and second sensing data based on secondsensing data based on the wireless signals transmitted between the threemotion sensing apparatus, and determine motion information of the userby a determining factor including the first sensing data and the secondsensing data.

It should be understood, however, that this Summary may not contain allof the aspects and embodiments of the present disclosure, is not meantto be limiting or restrictive in any manner, and that the invention asdisclosed herein is and will be understood by those of ordinary skill inthe art to encompass obvious improvements and modifications thereto.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings are included to provide a furtherunderstanding of the disclosure, and are incorporated in and constitutea part of this specification. The drawings illustrate embodiments of thedisclosure and, together with the description, serve to explain theprinciples of the disclosure.

FIG. 1 is a block diagram illustrating a motion tracking systemaccording to one of the exemplary embodiments of the disclosure.

FIG. 2 is a schematic diagram illustrating a motion tracking systemaccording to one of the exemplary embodiments of the disclosure.

FIG. 3 is a flowchart illustrating a motion tracking method according toone of the exemplary embodiments of the disclosure.

FIG. 4 is a schematic diagram illustrating a motion tracking methodaccording to one of the exemplary embodiments of the disclosure.

FIG. 5 is a schematic diagram illustrating a motion tracking methodaccording to one of the exemplary embodiments of the disclosure.

DESCRIPTION OF THE EMBODIMENTS

Reference will now be made in detail to the present preferredembodiments of the disclosure, examples of which are illustrated in theaccompanying drawings. Wherever possible, the same reference numbers areused in the drawings and the description to refer to the same or likeparts.

FIG. 1 is a block diagram illustrating a motion tracking system 10according to one of the exemplary embodiments of the disclosure.Referring to FIG. 1, the motion tracking system 10 includes, but notlimited to, three or more multiple motion sensing apparatuses 100, and acomputing apparatus 200. The motion tracking system 10 can be adaptedfor VR, AR, MR, XR or other reality related technology.

Each motion sensing apparatus 100 includes, but not limited to, awireless transceiver 110 and a motion sensor 130. The motion sensingapparatuses 100 could be a handheld controller or a wearable apparatus,such as a wearable controller, a smartwatch, an ankle sensor, a waistbelt, a head-mounted display (HMD), or the likes. In one embodiment,each motion sensing apparatus 100 is wearable on one human body portionof the user. The human body portion may be a hand, a head, an ankle, aleg, a waist, or other portions.

The wireless transceiver 110 could be a communication transceivercompatible with Bluetooth, Wi-Fi, IR, RFID, or other wirelesscommunication technologies. In one embodiment, the wireless transceiver110 is used for transmitting and/or receiving wireless signals with thewireless transceivers 110 of other motion sensing apparatuses 100, and asequence of first sensing data would be generated based on the wirelesssignals transmitted between the motion sensing apparatuses 100. Thedetailed process for the generation of the sequence of first sensingdata would be introduced later.

The motion sensor 130 may be an accelerometer, a gyroscope, amagnetometer, an inertial measurement unit (IMU), or any combination ofaforementioned sensors. In the embodiment, the motion sensor 130 is usedfor sensing the motion of a corresponding human body portion of theuser, which wears a motion sensing apparatus 100, for a time period, togenerate a sequence of first sensing data from the sensing result (suchas acceleration, rotation, magnetic force, etc.) of the motion sensor130 at multiple time points within the time period. For one example, thefirst sensing data includes a 3-degree of freedom (3-DoF) data, and the3-DoF data which are related to the orientation information of the humanbody portion in three-dimensional (3D) space, such as accelerations inyaw, roll, and pitch.

The computing apparatus 200 includes, but not limited to, a memory 240and a processor 250. The computing apparatus 200 could be a computer, aserver, a smartphone, a tablet, or one of the motion sensing apparatus100.

The memory 240 may be any type of a fixed or movable Random-AccessMemory (RAM), a Read-Only Memory (ROM), a flash memory or a similardevice or a combination of the above devices. The memory 240 can be usedto store program codes, device configurations, buffer data or permanentdata (such as sensing data, motion information, distance relationship,etc.), and these data would be introduced later.

The processor 250 is coupled to the memory 240, and the processor 250 isconfigured to load the program codes stored in the memory 240, toperform a procedure of the exemplary embodiment of the disclosure. Inone embodiment, functions of the processor 150 may be implemented byusing a programmable unit such as a central processing unit (CPU), amicroprocessor, a microcontroller, a digital signal processing (DSP)chip, a field programmable gate array (FPGA), etc. In some embodiment,the functions of the processor 250 may also be implemented by anindependent electronic device or an integrated circuit (IC), andoperations of the processor 150 may also be implemented by software.

It should be noticed that the processor 250 may or may not be disposedat the same apparatus with the one, part, or all of the motion sensingapparatuses 100. However, the apparatuses respectively equipped with themotion sensor 130 and the processor 250 may further includecommunication transceivers with compatible communication technology,such as Bluetooth, Wi-Fi, IR, or physical transmission line, totransmit/receive data with each other.

In one embodiment, the motion tracking system 10 may. further include ahead mounted display (HMD) 300. The HMD 300 is wearable on the head ofthe user. The HMD 300 includes, but not limited to, a wirelesstransceiver 310 and an image sensor 360.

The description of the wireless transceiver 310 could be referred to thedescription of the wireless transceiver 110, and would be omitted. Itmeans that HMD 300 may communicate with the motion sensing apparatus 100through the wireless transceiver 310.

The image sensor 360 may be a camera, such as a monochrome camera or acolor camera, a deep camera, a video recorder, or other sensor capableof capturing images.

FIG. 2 is a schematic diagram illustrating a motion sensing system 20according to one of the exemplary embodiments of the disclosure.Referring to FIG. 2, the motion sensing system 20 includes a HMD 300 andfour motion sensing apparatuses 100 (which are two ankle sensors worn onthe human body portions B1 and B2 (i.e., two ankles) and two handheldcontrollers worn on the human body portions B3 and B4 (i.e., twohands)). In some embodiments, the HMD 300 may further include anothermotion sensor 130 (not shown), to obtain orientation information ofhuman body portions B5 (i.e., the head). The processor 250 is embeddedin the HMD 300.

It should be noticed that the motion sensing system 20 is merely anexample to illustrate the disposing manners of motion sensingapparatuses 100, the HMD 300, and processor 250. However, there arestill many other implementations of the behavior understanding system10, and the present disclosure is not limited thereto.

To better understand the operating process provided in one or moreembodiments of the disclosure, several embodiments will be exemplifiedbelow to elaborate the operating process of the motion tracking system10 or 20. The devices and modules in the motion tracking system 10 or 20are applied in the following embodiments to explain the control methodprovided herein. Each step of the control method can be adjustedaccording to actual implementation situations and should not be limitedto what is described herein.

FIG. 3 is a flowchart illustrating a motion tracking method according toone of the exemplary embodiments of the disclosure. Referring to FIG. 3,the processor 250 may obtain first sensing data based on the motionsensors 130 disposed on the three motion sensing apparatuses 100 (stepS310). Specifically, regarding different types of the motion sensor 130,acceleration, rotation, magnetic force, orientation and/or 3-DoF/6-DoFfor the motion of corresponding human body portion in a 2D/3D space maybe obtained, and one or more sensing results of the motion sensor 130would become a sequence of first sensing data of the human body portion.

On the other hand, the processor 250 may obtain second sensing databased on wireless signals transmitted between the three motion sensingapparatuses 100 (step S330). In one embodiment, the processor 250 mayobtain the signal strengths of the wireless signals from three or moremotion sensing apparatuses 100 at multiple time points, and each signalstrength would be recorded with its corresponding transmitter andreceiver in the memory 240. The signal strength could be received signalstrength indication (RSSI), received channel power indicator (RCPI),reference signal received power (RSRP), or the likes. In one embodiment,the motion sensing apparatus 100 may monitor the signal strengths of alldetectable wireless signals, and each wireless signal includes specificidentifier(s) of the transmitter and/or the receiver. The motion sensingapparatus 100 may further feedback the signal strengths with thecorresponding identifier(s) of to the computing apparatus 200. Inanother embodiment, the computing apparatus 200 may monitor the signalstrengths of all detectable wireless signal, and the processor 250records the signal strengths with the corresponding identifier of thetransmitter in the memory 240. The signal strengths would be recordedfor a time period to generate a sequence of the second sensing data. Itmeans that the second sensing data includes a sequence of signalstrengths arranged by time.

In some embodiments, the processor 250 may further obtain third sensingdata based on the images captured from the image sensor 360. The thirdsensing data could be a sequence of images and/or sensing results (suchas brightness, color, depth, etc) of pixels in the images.

Then, the processor 250 may determine the motion information of the userby a determining factor including the first sensing data and the secondsensing data (step S350). In one embodiment, the motion information mayinclude the position information and the orientation information.Regarding the position information first, in one embodiment, theprocessor 250 may determine the position information of the useraccording to the first sensing data. In this embodiment, the determiningfactor includes the first sensing data. A displacement of acorresponding human body portion can be estimated through doubleintegral on the detected acceleration (i.e., the second sensing data) ofthe human body portion in three axes, to further determine the positioninformation based on the displacement. For example, the positioninformation could be coordinate at two or three axes, a positionrelative to a reference, etc.

In another embodiment, the processor 250 may obtain the positioninformation according to the second sensing data based on the wirelesssignals between three motion sensing apparatuses 100. In thisembodiment, the determining factor includes the second sensing data, itshould be noted that the signal strength of the wireless signal isrelated to a relative distance between two motion sensing apparatuses100. In addition, based on trilateration, three distances between threepoints can be used to determine the relative position information of thethree points. It is assumed that three of the motion sensing apparatuses100 as the aforementioned three points, the processor 250 may determinethe relative distances between each two motion sensing apparatuses 100as the distance relationship between the motion sensing apparatuses 100.Then, the processor 250 may generate the position information of thetracked apparatus based on the distance relationship and trilateration.

Taking the motion tracking system 20 as an example, the processor 250may obtain signal strengths of the wireless signal from the motionsensing apparatus 100 for the human body portion B3 to the HMD 300(which is one of the emotion sensing apparatus 100 in this embodiment)for the human body portion B5, the wireless signal from the motionsensing apparatus 100 for the human body portion B4 to the HMD 300 forthe human body portion B5, and the wireless signal from the motionsensing apparatus 100 for the human body portion B3 to the motionsensing apparatus 100 for the human body portion B4. The processor 250may determine their distance relationship according to the signalstrengths, and then generates the position information of the human bodyportion B3 based on the distance relationship. The position informationmay be coordinates or relative position.

It should be noted that the embodiment does not limit which three motionsensing apparatuses 100 are selected. For example, signal strengths ofthe wireless signal from the motion sensing apparatus 100 for the humanbody portion B2 to the motion sensing apparatus 100 for the human bodyportion B3, the wireless signal from the motion sensing apparatus 100for the human body portion B3 to the motion sensing apparatus 100 forthe human body portion B1, and the wireless signal from the motionsensing apparatus 100 for the human body portion B2 to the motionsensing apparatus 100 for the human body portion B1 can be used forestimating the position information of the human body portion B1. Thecombination of the motion sensing apparatuses 100 can be varied ondemand.

In still another embodiment, the processor 250 may determine theposition information of the user according to the third sensing data. Inthis embodiment, the determining factor includes the third sensing data.The position and the displacement of the human body portion in theimages can be used for determining the position information in the realenvironment. Taking FIG. 2 as an example, the sensing strength and thepixel position corresponding to the human body portion B4 in the imagecan be used for estimating depth information of the human body portionB4 (i.e., a distance relative to the HMD 300) and estimating 2D positionof the human body portion B4 at a plane parallel to the image sensor360.

It should be noted that the accuracy of the position information basedon merely one sensing manner, for example, which is based on one of thewireless transceiver 110, motion sensor 130, and the image sensor 360,may be different. Therefore, two or more sensing manners can be used todetermine the position information of the corresponding human bodyportion.

In one embodiment, the processor 250 may obtain first positioninformation according to the first sensing data, obtain second positioninformation according to the second sensing data, and obtain adjustedposition information according to the first position information and thesecond position information. In this embodiment, the determining factorincludes the first sensing data and the second sensing data. Theprocessor 250 may determine the position information according to acombination of the first position information and the second positioninformation. In some embodiments, the combination is a weightedcombination. The adjusted position information is determined accordingto the sum of weighted first position information and the weightedsecond position information.

In one embodiment, the weights of the weighted combination for the firstposition information and the second position information may be fixed.In another embodiment, the weights of the weighted combination for thefirst position information and the second position information may bevaried. The weight for the first position information could be a valuefrom 0 to 100%, and the weight for the second position information couldbe a value from 0 to 100%. However, the weights for the first and secondposition information both may not be 0 at the same time.

It should be noticed that in some embodiments, the position informationdetermined based on the third sensing data generated by the image of theimage sensor 360 may be more accurate than the position informationdetermined based on the wireless transceiver 110 and/or the motionsensor 130. Therefore, in one embodiment, the determining factor mayinclude the second and third sensing data. The processor 250 maydetermine the position information according to a combination of theposition information obtained based on the first, the second, and thethird sensing data.

In one embodiment, the processor 250 may obtain a first part of positioninformation according to the second sensing data in a first duration,obtain a second part of position information according to the thirdsensing data in a second duration, and combine the first and second partof position information as combined position information. The thirdsensing data, which detects the human body portions, can be used tocorrect position information based on the second sensing data in thefirst and second duration. The processor 250 may determine the combinedposition information based on the first and second part of positioninformation in different durations. For example, a position (1, 1) isdetermined based on the second sensing data at the first duration,another position (2, 1) is determined based on the third sensing data atthe second duration, and the combined position information may be adisplacement from the position (1, 1) to the position (2, 1).

In some embodiments, the processor 250 may determine the positioninformation according to a weighted combination of the second and thirdposition information. The weights for the second and third positioninformation may be varied or fixed based on the actual situations. Forexample, the weight for the third position information may be lager thanthe second position information. In another embodiment, the positioninformation is the weighted combination if the human body portions existin the third sensing data, and the position is the second positioninformation if the human body portions do not exist in the third sensingdata.

In one embodiment, the image sensor 360 may be designed with a specificfield of view (FOV). If one human body portion is located outside of thefield of view of the image sensor 360, the processor 250 may not able todetermine the motion information of this human body portion merely usingthe third sensing data, and the first or second sensing data should beconsidered.

In one embodiment, the processor 250 may determine whether one humanbody portion of the user exists in the sequence of third sensing data,and determine whether to use the distance relationship between threemotion sensing apparatuses 100 according to a determined result of theexistence of the human body portion to determine the positioninformation based on trilateration. The processor 250 may use machinelearning technology (such as deep learning, artificial neural network(ANN), or support vector machine (SVM), etc.) to identify the targethuman body portion in the third sensing data.

FIG. 4 is a schematic diagram illustrating a motion tracking methodaccording to one of the exemplary embodiments of the disclosure.Referring to FIG. 4, it is assumed that the motion sensing apparatus 100for the human body portion B4 is the target apparatus. In this figure,the human body portion B4 exists in the field of view FOV of HMD 300(i.e., the human body portion B4 exists in the third sensing data).

FIG. 5 is a schematic diagram illustrating a motion tracking methodaccording to one of the exemplary embodiments of the disclosure.Referring to FIG. 5, it is assumed that the motion sensing apparatus 100for the human body portion B3 is the target apparatus. In this figure,the human body portion B5 does not exist in the field of view FOV of HMD300 (i.e., the human body portion B3 does not exist in the third sensingdata).

It should be noticed that the size and the shape of the field of viewillustrated in FIGS. 4 and 5 are merely an example and could be modifiedbased on actual requirements.

Therefore, the field of view of the image sensor 360 is used todetermine whether the human body portions exist in the third sensingdata. In one embodiment, it is assumed that the human body portions arelocated outside of the field of view (i.e., not exist in the thirdsensing data) at the first duration, and the human body portions arelocated inside of the field of view (i.e., exist in the third sensingdata) of the image sensor 360 at the second duration. In someembodiments, it is assumed that the human body portions are locatedinside of the field of view of the image sensor 360 at the first andsecond duration.

In another embodiment, the processor 250 may obtain first positioninformation according to the first sensing data, obtain second positioninformation according to the second sensing data, obtain third positioninformation according to the third sensing data, and obtain obtainingadjusted position information according to the first positioninformation, the second position information and the third positioninformation. In this embodiment, the determining factor includes thefirst, second, and third sensing data. The processor 250 may determinethe adjusted position information according to a combination of thefirst motion information, the second motion information, and the thirdposition information.

In one embodiment, the combination is a weighted combination. Theprocessor 250 may determine a first weight for the first positioninformation and a second weight for the second position informationaccording to the third position information. In one embodiment, thefirst weight and the second weight are varied time after time. In theduration that the human body portions exist in the third sensing data,the third position information would be considered as correct positioninformation, and the weighted combination of the first and secondposition information with the first weight and the second weight wouldbe adjusted according to the third position information. It should benoted that the processor 250 may obtain a first parameter by multiplyingthe first weight and the first position information, obtain a secondparameter by multiplying the second weight and the second positioninformation, and obtain the adjusted position information by adding thefirst parameter to the second parameter, so as to obtain the weightedcombination.

In one embodiment, the first and second weights at a subsequent timepoint may be determined based on an equation that the third positioninformation equals the weighted combination of the first and secondposition information at a previous time point. For example, at the thirdtime point, the first weight is 0.5 and the second weight is 0.5, thefirst position information is (6, 6, 6) and the second positioninformation is (10, 10, 10) in a 3-dimension coordinate system, and theadjust position information would be (8, 8, 8). If the third positioninformation is (7, 7, 7), the first weight and second weights at thefourth time point would be determined as 0.75 and 0.25,respectively.Then, at the fourth time point, if the first position information is (7,6, 6) and the second position information is (12, 10, 10) in a3-dimension coordinate system, and the adjust position information wouldbe (8.25, 7, 7).

In another embodiment, the first and second weights at a current timepoint may be determined based on an equation that the third positioninformation equals the weighted combination of the first and secondposition information at the current time point. For example, at thesecond time point, the first position information is (6, 6, 6) and thesecond position information is (10, 10, 10) in a 3-dimension coordinatesystem. If the third position information is (7, 7, 7), the first weightand second weights at the second time point would be determined as 0.75and 0.25, respectively. Then, the adjust position information at thesecond time point would be determined as (7, 7, 7).

In some embodiments, the first weight and the second weight are fixed ifthe human body portions of the user do not exist in the third sensingdata. If the human body portions are located outside of the field ofview of the image sensor 360, the third and second weights would be thesame as the previous first and second weights at a previous time pointwhen the human body portions of the user still exist in the thirdsensing data. For example, the human body portions are located insidethe field of view of the image sensor 360 at the first time point, andthe first weight is 0.5 and the second weight is 0.5. Then, at thesecond time point, the human body portions are located outside of thefield of view of the image sensor 360. The first weight would be 0.5 andthe second weight would be 0.5 at the second time point as same as thefirst and second weights at the first time point. Until the human bodyportions of the user exist in the third sensing data, the first andsecond weights would be varied according to the third sensing data.

In still another embodiment, the processor 250 may determine theadjusted position information according to a weighted combination of thefirst position information, the second position information, and thethird position information. The adjusted position information isdetermined according to the sum of weighted first position information,the weighted second position information, and the weighted thirdposition information. The weights for the three pieces of positioninformation may be varied or fixed based on the actual situations.

On the other hand, regarding the orientation information, in oneembodiment, the processor 250 may use the sequence of the first sensingdata as the orientation information directly. For example, theorientation information could be the acceleration, the angular velocityin the three-axis, the orientation, 3-DoF information and/or 6-DoFinformation.

In another embodiment, the processor 250 may determine the orientationinformation according to the third sensing data. Taking FIG. 4 as anexample, two poses of the human body portion B4 in the images atdifferent time points can be used for estimating the orientationinformation.

In some embodiment, the processor 250 may determine the orientationinformation according to the first sensing data and the third sensingdata. The orientation information may be a weighted combination of thefirst sensing data and the third sensing data. For example, the positioninformation is determined according to the sum of weighted firstorientation information based on the motion sensor 130 and the weightedsecond orientation information based on the image sensor 360.

In one embodiment, the field of view of the image sensor 360 would be acondition about whether to use the orientation information according tothe third sensing data. If the human body portions exist in the thirdsensing data, the orientation information may be determined according tothe first sensing data and the third sensing data. If the human bodyportions do not exist in the third sensing data, the orientationinformation may be determined merely according to the first sensingdata.

In one embodiment, the processor 250 may determine the motioninformation of the user according to both the orientation informationand the position information. The orientation information could begenerated based on the first sensing data, the third sensing data, orthe combination of the first and third sensing data as mentioned above.The position information could be generated based on one of the first,second and third sensing data as mentioned above. Taking the human bodyportion B1 or B2 in FIG. 2 as an example, the motion information may berelated to lifting, pointing, kicking, stepping, or jumping motion.

In another embodiment, the processor 250 may determine the motioninformation of the user according to both the orientation informationbased on the first sensing data and the adjusted position informationbased on the first and second position information. No matter the humanbody portions exist in the third sensing data, the processor 250 canpredict the motion of the user.

In still another embodiment, the processor 250 may determine the motioninformation of the user according to both the orientation informationbased on the first sensing data and the combined position informationbased on the second and third sensing data. It means that the motioninformation can be determined based on the orientation information andthe combined position information in two durations when the human bodyportions exist and do not exist in the third sensing data.

Taking FIGS. 4 and 5 as an example, hands up motion for the human bodyportion B4 is determined in FIG. 4, and hands down motion is determinedin FIG. 5. Then, a swing motion from up to down for the human bodyportion B4 is determined.

In one embodiment, the processor 250 may determine the motioninformation of the user merely according to the position informationbased on the second sensing data. In another embodiment, the processor250 may determine the motion information of the user merely according tothe combined position information based on the second and third sensingdata. In some embodiments, the processor 250 may determine the motioninformation of the user merely according to the position informationbased on the second sensing data if the human body portions do not existin the third sensing data, and the may determine the motion informationof the user merely according to the position information based on thethird sensing data or the combined position information if the humanbody portions exist in the third sensing data.

The displacement or trajectory of the human body portion may be tracked,and the motion information can be determined based on the displacementor trajectory. Taking FIGS. 4 and 5 as an example, the human bodyportion B3 moves from up to down, and a swing motion from up to down forthe human body portion B4 is determined.

It will be apparent to those skilled in the art that variousmodifications and variations can be made to the structure of the presentdisclosure without departing from the scope or spirit of the disclosure.In view of the foregoing, it is intended that the present disclosurecover modifications and variations of this disclosure provided they fallwithin the scope of the following claims and their equivalents.

What is claimed is:
 1. A motion tracking method, adapted for a motiontracking system, wherein the motion tracking system comprises first,second and third motion sensing apparatuses wearable on human bodyportions of a user, and the motion tracking method comprises: obtainingfirst sensing data based on motion sensors disposed on the first, secondand third motion sensing apparatuses; obtaining second sensing databased on wireless signals transmitted between the first, second andthird motion sensing apparatuses; and determining motion information ofthe user by a determining factor, wherein the determining factorcomprises the first sensing data and the second sensing data.
 2. Themotion tracking method according to claim 1, the step of determining themotion information of the user comprises: obtaining orientationinformation according to the first sensing data; obtaining positioninformation according to the second sensing data; and determining themotion information of the user according to both the orientationinformation and the position information.
 3. The motion tracking methodaccording to claim 1, the step of determining the motion information ofthe user comprises: obtaining first position information and orientationinformation according to the first sensing data; obtaining secondposition information according to the second sensing data; obtainingadjusted position information according to the first positioninformation and the second position information; and determining themotion information of the user according to both the orientationinformation and the adjusted position information.
 4. The motiontracking method according to claim 1, further comprising: obtainingthird sensing data based on images captured from an image sensor,wherein the human body portions of the user exist in the third sensingdata, and the determining factor further comprises the third sensingdata.
 5. The motion tracking method according to claim 4, the step ofdetermining the motion information of the user comprises: obtainingorientation information according to the first sensing data; obtaining afirst part of position information according to the second sensing datain a first duration; obtaining a second part of position informationaccording to the third sensing data in a second duration; combining thefirst and second part of position information as combined positioninformation; and determining the motion information of the useraccording to both the orientation information and the combined positioninformation.
 6. The motion tracking method according to claim 4, thestep of determining the motion information of the user comprises:obtaining orientation information and first position informationaccording to the first sensing data; obtaining second positioninformation according to the second sensing data; obtaining thirdposition information according to the third sensing data; obtainingadjusted position information according to the first positioninformation, the second position information and the third positioninformation; and determining the motion information of the useraccording to both the orientation information and the adjusted positioninformation.
 7. The motion tracking method according to claim 6, whereinthe step of obtaining the adjusted position information according to thefirst position information, the second position information and thethird position information comprises: determining a first weight and asecond weight according to the third position information; obtaining afirst parameter by multiplying the first weight and the first positioninformation; obtaining a second parameter by multiplying the secondweight and the second position information; and obtaining the adjustedposition information by adding the first parameter to the secondparameter.
 8. The motion tracking method according to claim 7, whereinthe first weight and the second weight are varied time after time. 9.The motion tracking method according to claim 7, wherein the firstweight and the second weight are fixed in response to the human bodyportions of the user not existing in the third sensing data.
 10. Themotion tracking method according to claim 5, wherein the human bodyportions of the user do not exist in the third sensing data at the firstduration, and the human body portions of the user exist in the thirdsensing data at the second duration.
 11. A motion tracking system,comprising: three motion sensing apparatuses, wearable on human bodyportions of a user, wherein each of the motion sensing apparatusescomprising: a wireless transceiver, transmitting or receiving wirelesssignals; and a motion sensor, sensing motion of one of the human bodyportions of the user; and a processor, configured to perform: obtainingfirst sensing data based on the motion sensors of the three motionsensing apparatuses; obtaining second sensing data based on the wirelesssignals transmitted between the three motion sensing apparatuses; anddetermining motion information of the user by a determining factor,wherein the determining factor comprises the first sensing data and thesecond sensing data.
 12. The motion tracking system according to claim11, wherein the processor is configured to perform: obtainingorientation information according to the first sensing data; obtainingposition information according to the second sensing data; anddetermining the motion information of the user according to both theorientation information and the position information.
 13. The motiontracking system according to claim 11, wherein the processor isconfigured to perform: obtaining first position information andorientation information according to the first sensing data; obtainingsecond position information according to the second sensing data;obtaining adjusted position information according to the first positioninformation and the second position information; and determining themotion information of the user according to both the orientationinformation and the adjusted position information.
 14. The motiontracking system according to claim 11, further comprising: an imagesensor, obtaining images; wherein the processor is configured toperform: obtaining third sensing data based on the images, wherein thehuman body portions of the user exist in the third sensing data, and thedetermining factor further comprises the third sensing data.
 15. Themotion tracking system according to claim 14, wherein the processor isconfigured to perform: obtaining orientation information according tothe first sensing data; obtaining a first part of position informationaccording to the second sensing data in a first duration; obtaining asecond part of position information according to the third sensing datain a second duration; combining the first and second part of positioninformation as combined position information; and determining the motioninformation of the user according to both the orientation informationand the combined position information.
 16. The motion tracking systemaccording to claim 14, wherein the processor is configured to perform:obtaining orientation information and first position informationaccording to the first sensing data; obtaining second positioninformation according to the second sensing data; obtaining thirdposition information according to the third sensing data; obtainingadjusted position information according to the first positioninformation, the second position information and the third positioninformation; and determining the motion information of the useraccording to both the orientation information and the adjusted positioninformation.
 17. The motion tracking system according to claim 16,wherein the processor is configured to perform: determining a firstweight and a second weight according to the third position information;obtaining a first parameter by multiplying the first weight and thefirst position information; obtaining a second parameter by multiplyingthe second weight and the second position information; and obtaining theadjusted position information by adding the first parameter to thesecond parameter.
 18. The motion tracking system according to claim 17,wherein the first weight and the second weight are varied time aftertime.
 19. The motion tracking system according to claim 17, wherein thefirst weight and the second weight are fixed in response to the humanbody portions of the user not existing in the third sensing data. 20.The motion tracking system according to claim 15, wherein the human bodyportions of the user do not exist in the third sensing data at the firstduration, and the human body portions of the user exist in the thirdsensing data at the second duration.